Murray-Smith, R., Neumerkel, D., and Sbarbaro-Hofer, D. (1992) Neural networks for modelling and control of a non-linear dynamic system. In: IEEE International Symposium on Intelligent Control, 11-13 August 1992, Glasgow, Scotland.
Publisher's URL: http://dx.doi.org/10.1109/ISIC.1992.225125
The authors describe the use of neural nets to model and control a nonlinear second-order electromechanical model of a drive system with varying time constants and saturation effects. A model predictive control structure is used. This is compared with a proportional-integral (PI) controller with regard to performance and robustness against disturbances. Two feedforward network types, the multilayer perceptron and radial-basis-function nets, are used to model the system. The problems involved in the transfer of connectionist theory to practice are discussed.
|Item Type:||Conference Proceedings|
|Glasgow Author(s) Enlighten ID:||Murray-Smith, Professor Roderick|
|Authors:||Murray-Smith, R., Neumerkel, D., and Sbarbaro-Hofer, D.|
|Subjects:||T Technology > TK Electrical engineering. Electronics Nuclear engineering|
|College/School:||College of Science and Engineering > School of Computing Science|
|Publisher:||Institute of Electrical and Electronics Engineers (IEEE)|
|Copyright Holders:||Copyright © 1992 Institute of Electrical and Electronics Engineers (IEEE)|
|First Published:||First published in Proceedings of the 1992 IEEE International Symposium on Intelligent Control|
|Publisher Policy:||Reproduced in accordance with the copyright policy of the publisher|